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At least 253 records · Page 14

Tethered balloon measurements reveal enhanced aerosol occurrence aloft interacting with Arctic low-level clouds

Low-level clouds in the Arctic affect the surface energy budget and vertical transport of heat and moisture. The limited availability of cloud-droplet-forming aerosol particles strongly impacts cloud properties and lifetime. Vertical particle distributions are required to study aerosol–cloud interaction over sea ice comprehensively. This article presents vertically resolved measurements of aerosol particle number concentrations and sizes using tethered balloons. The data were collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition in the summer of 2020. Thirty-four profiles of aerosol particle number concentration were observed in 2 particle size ranges: 12–150 nm (N 12−150 ) and above 150 nm (N >150 ). Concurrent balloon-borne meteorological measurements provided context for the continuous profiles through the cloudy atmospheric boundary layer. Radiosoundings, cloud remote sensing data, and 5-day back trajectories supplemented the analysis. The majority of aerosol profiles showed more particles above the lowest temperature inversion, on average, double the number concentration compared to below. Increased N 12−150 up to 3,000 cm −3 were observed in the free troposphere above low-level clouds related to secondary particle formation. Long-range transport of pollution increased N >150 to 310 cm −3 in a warm, moist air mass. Droplet activation inside clouds caused reductions of N >150 by up to 100%, while the decrease in N 12−150 was less than 50%. When low-level clouds were thermodynamically coupled with the surface, profiles showed 5 times higher values of N 12−150 in the free troposphere than below the cloud-capping temperature inversion. Enhanced N 12−150 and N >150 interacting with clouds were advected above the lowest inversion from beyond the sea ice edge when clouds were decoupled from the surface. Vertically discontinuous aerosol profiles below decoupled clouds suggest that particles emitted at the surface are not transported to clouds in these conditions. It is concluded that the cloud-surface coupling state and free tropospheric particle abundance are crucial when assessing the aerosol budget for Arctic low-level clouds over sea ice.

54 ENVIRONMENTAL SCIENCES↗

AERACEPT (AErosol Rapid Analysis Combined Entry Probe/sonde Technology) for the Nephele Venus Cloud Mission Concept

Nephele is a small atmospheric probe mission concept to determine whether the Venus clouds contain organic matter. Nephele complements larger missions that seek to conduct Venus atmospheric analyses, such as DAVINCI, Venera-D, and the Morning Star missions, by directly sampling and analyzing cloud and haze particles. AERACEPT is an aerosol sampling technology designed to minimize the mass, volume, and complexity required for in situ planetary atmosphere characterization. A single aeroshell functions as a combined entry vehicle, descent probe, and instrumented sonde, combining recent advances in thermal protection materials with heritage technology from planetary and airborne science. The velocity of descent drives aerosol through inlets embedded in the aeroshell’s thermal protection material; inertial separation isolates the particles from the gas stream; and the particle capture surface doubles as the analysis substrate. This method can work without heat shield separation, descent control, or active sample handling; these advantages trade against a smaller sample volume, higher risk of sample heating, and shorter time for analysis and data return. AERACEPT further benefits from modeling of the internal and external flow to understand the particle capture efficiency and bias for size and concentration distributions. AERACEPT is well suited for a Venus mission such as Nephele, where a passive descent trajectory is both subsonic over the altitudes of interest and provides sufficient velocity and pressure differential for the particle sizes of interest. A thermal and flow toolchain developed in-house (Traj→ DPLR→ PATO→ openFOAM) was used to model an 80-cm aeroshell with science operations 63–39 km. These models indicate that AERACEPT will provide ~24 µL accumulated sample of particles ≥ 0.2 µm, substantially above the 2 µL threshold requirement. The worst-case particle heating will be ~14 K above ambient, for the smallest particles at the lowest altitude; most particles will experience ≤ 1 K rise, at which almost all analytes of interest will be unaffected. Plasma jet testing of a small-scale aeroshell-material inlet was recently conducted to validate the thermal model parameters; wind tunnel testing to validate the flow model parameters is underway.

AERACEPT↗

Systematic characterization of unknown compounds via dimensionality reduction of time series

Analysis of ambient aerosols provides valuable insight into particle sources and formation chemistry. However, due to the complexity of atmospheric data and the dynamic nature of aerosol composition, a substantial fraction of data often become discarded by conventional analysis methods. Furthermore, a large fraction of chemical species within those data are unidentifiable due to a lack of matching spectral information, resulting in suboptimal characterization of chemical composition. Previous work has demonstrated techniques for cataloging analytes in a chromatographic dataset by deconvolution of mass spectra, but integration of these analytes throughout a large dataset remains time consuming. Here, we present a method to automatically identify an ion for quantitation for single-ion chromatogram based peak fitting and integration, enabling comprehensive integration of analytes with minimal user interaction. The resulting time series are clustered with a machine-learning based dimensionality reduction technique to systematically investigate the underlying characteristics of the categorized analytes and gain new insights into the chemical composition and physicochemical properties of the unidentifiable analytes. We apply these methods to existing atmospheric datasets collected in Manacapuru, Brazil during the GoAmazon2014/5 campaign to identify new analytes and interpret their variability and transformations in the atmosphere. The analysis results generate 408 time series from cataloged analytes of interest, and the clustering of those time series with spherical k-means results in 8 distinct clusters. We find the analytes form clusters based on their distinct physicochemical properties, demonstrating the method’s ability to systematically identify and selectively filter contaminants and instrumental analytes and characterize the unidentifiable analytes.

54 ENVIRONMENTAL SCIENCES↗

Machine learning for single-ended event reconstruction in PROSPECT experiment

The Precision Reactor Oscillation and Spectrum Experiment, PROSPECT, was a segmented antineutrino detector that successfully operated at the High Flux Isotope Reactor in Oak Ridge, TN, during its 2018 run. Despite challenges with photomultiplier tube base failures affecting some segments, innovative machine learning approaches were employed to perform position and energy reconstruction, and particle classification. This work highlights the effectiveness of convolutional neural networks and graph convolutional networks in enhancing data analysis. By leveraging these techniques, a 3.3% increase in effective statistics was achieved compared to traditional methods, showcasing their potential to improve analysis performance. Furthermore, these machine learning methodologies offer promising applications for other segmented particle detectors, underscoring their versatility and impact.

47 OTHER INSTRUMENTATION↗

Investigating Particle-Particle Electrostatic Effects on Charged Lunar Dust Transport via Discrete Element Modeling

NASA surface exploration missions have always seen negative effects of dust including the Apollo missions. The astronaut-witnessed unusual behavior of the dust particles that surround the vehicle after engine cutoff has the potential to have more of an influence on surface systems dust loading than the high velocity lunar rocket plume ejecta in the landing process. The levitation and transport of the fine components of regolith on lunar surface has been linked to electrostatic effects and electric field, but so far there is no accurate model considering the inter-particle electrostatic interactions, especially when the particles are charged by rocket plume or other mechanical interactions due to exploration activities. This study is proposed to investigate the dynamics of charged lunar regolith with a discrete element method (DEM) approach focusing on the inter-particle interactions and contact charge transfer. The grain dynamics is coupled with mechanical and electrical particle interactions, and both short- and long-range interactions between spherical particles are incorporated. A tribo-charging model based on instantaneous collisions between particles is adopted and validated by comparing the simulation results to existing experimental data. Sensitivity analysis is conducted to quantify the effects of initial charge, tribo-charging, and E-field on transport of lunar dust based on JSC-1 simulants with a radius of 50 lm. DEM simulations are also conducted in a near realistic lunar environment with the estimations of initial conditions that shows the difference in position and velocity distributions between charged particles and uncharged particles. The results indicate that the charged dust particles have higher dispersion of position and velocity by several orders of magnitude due to electrostatic effects. This provides a potential explanation for the phenomena of the approximately 30 s dust lofting following Apollo Lunar Module landing.

Lunar dust↗

Effect of solvothermal synthesis parameters on the crystallite size and atomic structure of cobalt iron oxide nanoparticles

We here investigate how the synthesis method affects the crystallite size and atomic structure of cobalt iron oxide nanoparticles. By using a simple solvothermal method, we first synthesized cobalt ferrite nanoparticles of ca. 2 and 7 nm, characterized by Transmission Electron Microscopy (TEM), Small Angle X-ray scattering (SAXS), X-ray and neutron total scattering. The smallest particle size corresponds to only a few spinel unit cells. Nevertheless, Pair Distribution Function (PDF) analysis of X-ray and neutron total scattering data shows that the atomic structure, even in the smallest nanoparticles, is well described by the spinel structure, although with significant disorder and a contraction of the unit cell parameter. These effects can be explained by the surface oxidation of the small nanoparticles, which is confirmed by X-ray near edge absorption spectroscopy (XANES). Neutron total scattering data and PDF analysis reveal a higher degree of inversion in the spinel structure of the smallest nanoparticles. Neutron total scattering data also allow magnetic PDF (mPDF) analysis, which shows that the ferrimagnetic domains correspond to ca. 80% of the crystallite size in the larger particles. A similar but less well-defined magnetic ordering was observed for the smallest nanoparticles. Finally, we used a co-precipitation synthesis method at room temperature to synthesize ferrite nanoparticles similar in size to the smallest crystallites synthesized by the solvothermal method. Structural analysis with PDF demonstrates that the ferrite nanoparticles synthesized via this method exhibit a significantly more defective structure compared to those synthesized via a solvothermal method.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Multiwavelength investigations of PKS 2300–18: S-shaped radio quasar with precessing jets and double-peaked broad emission-line spectrum

ABSTRACT S-shaped radio galaxy jets are prime sources for investigating the dynamic interplay between the central active galactic nucleus (AGN), the jets, and the ambient intergalactic medium. These sources are excellent candidates for studying jet precession, as their S-shaped inversion symmetry strongly indicates underlying precession. We present a multiwavelength analysis of the giant inversion-symmetric S-shaped radio galaxy PKS 2300$-$18, which spans 0.76 Mpc. The host is a quasar at a redshift of 0.128, displaying disturbed optical morphology due to an ongoing merger with a companion galaxy. We conducted a broad-band radio spectral study using multifrequency data ranging from 183 MHz to 6 GHz, incorporating dedicated observations with the upgraded Giant Metrewave Radio Telescope (uGMRT) and Karl G. Jansky Very Large Array (JVLA) alongside archival radio data. A particle injection model was fitted to the spectra of different regions of the source to perform ageing analysis, which was supplemented with a kinematic jet precession model. The ageing analysis revealed a maximum plasma age of $\sim$ 40 Myr, while the jet precession model indicated a precession period of $\sim$ 12 Myr. ROentgen SATellite (ROSAT) data revealed an X-ray halo of Mpc size, and from Chandra the AGN X-ray spectrum was modelled using thermal and power-law components. The optical spectrum displaying double-peaked broad emission lines was modelled, indicating complex broad-line region kinematics at the centre with the possibility of a binary SMBH. We present the results of our multiwavelength analysis of the source, spanning scales from a few light-days to a few Mpc, and discuss its potential evolutionary path.

Misra, Arpita↗

Simulating Electron Distribution Function in the Pulsating Aurora Using Particle and Wave Data of ARASE Satellite

Decades lasting research on the pulsating aurora suggested that this phenomenon forms as result of interactions between the magnetospheric keVs electrons and whistler-mode chorus waves. Arase satellite observation reported the direct evidence for this process confirming in situ measurement of highly correlated precipitated electrons and chorus wave activity. This paper presents the theoretical analysis of this observational event based on the SuperThermal Electron Transport (STET) code that simulates the highly dynamic environment of measured waves and particle data. Specifically, the STET code simulated results confirms the delicate loss-cone observation results of this mission and further reveals the broader energy range of precipitated electron fluxes that was not measurable by Arase satellite.

George V Khazanov↗

Leveraging unlabeled SEM datasets with self-supervised learning for enhanced particle segmentation

Scanning Electron Microscopes (SEMs) are widely used in experimental science laboratories, often requiring cumbersome and repetitive user analysis. Automating SEM image analysis processes is highly desirable to address this challenge. In particle sample analysis, Machine Learning (ML) has emerged as the most effective approach for particle segmentation. However, the time-intensive process of manually annotating thousands of SEM images limits the applicability of supervised learning approaches. Self-Supervised Learning (SSL) offers a promising alternative by enabling knowledge extraction from raw, unlabeled data. This study presents a framework for evaluating SSL techniques in SEM image analysis, focusing on novel methods leveraging the ConvNeXtV2 architecture for particle detection. A dataset comprising 25,000 SEM images is curated to benchmark these proposed SSL methods. The results demonstrate that ConvNeXtV2 models, with varying parameter counts, consistently outperform other techniques in particle detection across different length scales, achieving up to a 34% reduction in relative error compared to established SSL methods. Furthermore, an ablation study explores the relationship between dataset size and SSL performance, providing actionable insights for practitioners regarding model selection and resource efficiency. This research advances the integration of SSL into autonomous analysis pipelines and supports its application in accelerating materials science discovery.

Rettenberger, Luca↗

Search for heavy long-lived charged particles with level-1 trigger scouting data from proton-proton collisions at $\sqrt{s} = 13.6$ TeV

A search for heavy long-lived charged particles at the LHC is presented. Particles interacting with the CMS muon detector across several bunch crossings are searched for using a data sample of proton-proton collisions at $\sqrt{s}$ = 13.6 TeV collected with the CMS detector in 2024, corresponding to an integrated luminosity of 3.7 fb$^{-1}$. This is the first search relying on the novel level-1 trigger scouting data set collected without any trigger selection, allowing correlations between bunch crossings to be analyzed. The results are interpreted as upper limits on the cross sections of several benchmark processes with pair production of heavy long-lived charged particles. Upper limits on the fiducial cross section of a heavy long-lived charged particle with $p_\mathrm{T}$$\gt$ 500 GeV and $\lvertη\rvert$$\lt$ 0.83 are also set in different ranges of $β=v/c$. This analysis is a crucial proof of concept for the level-1 trigger data scouting system and complements existing searches for heavy long-lived charged particles by extending the sensitivity to lower $β$ values.

CMS↗

Bow shock protons in the lunar environment

Protons from the earth's bow shock are observed by the suprathermal ion detector experiment (SIDE) in two regions of the lunar orbit. The dawn region begins at the dawn-side bow-shock crossing and ends about 5 days later, the dusk region begins at about 2 days prior to entering the dusk-side magnetosheath and ends at the inbound bow-shock crossing. Dusk and dawn refer to a terrestrial coordinate system. The dominant contribution to the ion spectra observed by the SIDE in these regions is from particles with energies between about 750 eV/q and 3500 eV/q. Analysis of simultaneous data from the Explorer 35 magnetometer and the SIDE indicates that the observability of bow-shock protons at the lunar distance is dependent on the configuration of the interplanetary magnetic field.

Benson, J.↗

Software manual for operating particle displacement tracking data acquisition and reduction system

The software manual is presented. The necessary steps required to record, analyze, and reduce Particle Image Velocimetry (PIV) data using the Particle Displacement Tracking (PDT) technique are described. The new PDT system is an all electronic technique employing a CCD video camera and a large memory buffer frame-grabber board to record low velocity (less than or equal to 20 cm/s) flows. Using a simple encoding scheme, a time sequence of single exposure images are time coded into a single image and then processed to track particle displacements and determine 2-D velocity vectors. All the PDT data acquisition, analysis, and data reduction software is written to run on an 80386 PC.

Wernet, Mark P.↗

Shuttle Hypervelocity Impact Database

With three flights remaining on the manifest, the shuttle impact hypervelocity database has over 2800 entries. The data is currently divided into tables for crew module windows, payload bay door radiators and thermal protection system regions, with window impacts compromising just over half the records. In general, the database provides dimensions of hypervelocity impact damage, a component level location (i.e., window number or radiator panel number) and the orbiter mission when the impact occurred. Additional detail on the type of particle that produced the damage site is provided when sampling data and definitive analysis results are available. The paper will provide details and insights on the contents of the database including examples of descriptive statistics using the impact data. A discussion of post flight impact damage inspection and sampling techniques that were employed during the different observation campaigns will be presented. Future work to be discussed will be possible enhancements to the database structure and availability of the data for other researchers. A related database of ISS returned surfaces that are under development will also be introduced.

Hyde, James I.↗

Shuttle Hypervelocity Impact Database

With three missions outstanding, the Shuttle Hypervelocity Impact Database has nearly 3000 entries. The data is divided into tables for crew module windows, payload bay door radiators and thermal protection system regions, with window impacts compromising just over half the records. In general, the database provides dimensions of hypervelocity impact damage, a component level location (i.e., window number or radiator panel number) and the orbiter mission when the impact occurred. Additional detail on the type of particle that produced the damage site is provided when sampling data and definitive analysis results are available. Details and insights on the contents of the database including examples of descriptive statistics will be provided. Post flight impact damage inspection and sampling techniques that were employed during the different observation campaigns will also be discussed. Potential enhancements to the database structure and availability of the data for other researchers will be addressed in the Future Work section. A related database of returned surfaces from the International Space Station will also be introduced.

Hyde, James L.↗

Oxychlorine Species on Mars: The Gale Crater Story

Comparing data from the Alpha- Particle X-Ray Spectrometer (APXS) and the Sample Analysis at Mars (SAM) instruments on MSL reveals a strong linear correlation between chlorine and oxygen, further demonstrating the presence of oxychlorine species in Gale Crater and, very likely, globally on Mars. Perchlorate was first discovered on Mars by the Microscopy, Electrochemistry, and Conductivity Analyzer (MECA) instrument on the Phoenix lander in 2008. Current hypotheses suggest that the formation of oxychlorine species such as perchlorate or chlorate is a global process and that these species should be globally distributed on Mars [e.g. 2-4]. To date, the SAM and Chemistry and Mineralogy (CheMin) instruments on MSL have analyzed one scooped sample of aeolian material (Rocknest [RN]), and four drilled samples (John Klein [JK], Cumberland [CB], Windjana [WJ], and Confidence Hills [CH]). The APXS instrument has also investigated the same or very similar samples. Although not definitively identified, oxychlorine species have been proposed to explain releases of O2, HCl, and chlorinated hydrocarbon species detected by evolved gas analysis (EGA) with the SAM instrument. We report a strong linear correlation between wt. % Cl detected by APXS and moles O2 detected by SAM during pyrolysis, indicating the presence of oxychlorine species in Gale Crater.

Archer, P. D., Jr.↗

An estimate of particle flux from Pioneer 8 and 9 part 2

Five years of particle impact data obtained from Pioneer 8 and 9 have established reliable frequency levels for the near ecliptic region covered. This analysis is concerned with obtaining a multiplier which permits an estimate of the particle flux through a 1-A.U. sphere centered at the sun.

Wolf, H.↗

Plasma sheet at lunar distance - Characteristics and interactions with the lunar surface

The plasma sheet at lunar distance is investigated with the use of data from the charged particle lunar environment experiment (CPLEE), complemented with data from the Explorer 35/ARC magnetometer. It is shown that the presence of the lunar surface does not appreciably affect measurements of the plasma sheet characteristics by the lunar-based CPLEE instrument. In particular, the lunar surface generally does not shadow plasma sheet particles. This may be due to rapid random passage (greater than 40 km/sec) of magnetotail field lines with respect to the lunar surface or to diffusion of plasma sheet electrons into the flux tubes in contact with the lunar surface. The plasma sheet is generally observed as a rapid increase in observed particle fluxes and a simultaneous decrease in field strength. A statistical analysis of the CPLEE data shows that the plasma sheet in the midnight sector has a thickness of 5 R sub E plus or minus 2 R sub E. Geomagnetic activity reduces the probability of encounters between the moon and the plasma sheet.

Rich, F. J.↗

Chandra Radiation Environment Modeling

CRMFLX (Chandra Radiation Model of ion FluX) is a radiation environment risk mitigation tool for use as a decision aid in planning the operations times for Chandra's Advanced CCD Imaging Spectrometer (ACIS) detector. The accurate prediction of the proton flux environment with energies of 100 - 200 keV is needed in order to protect the ACIS detector against proton degradation. Unfortunately, protons of this energy are abundant in the region of space Chandra must operate, and on-board particle detectors do not measure proton flux levels of the required energy range. This presentation will describe the plasma environment data analysis and modeling basis of the CRMFLX engineering environment model developed to predict the proton flux in the solar wind, magnetosheath, and magnetosphere phenomenological regions of geospace. The recently released CRMFLX Version 2 implementation includes an algorithm that propagates flux from an observation location to other regions of the magnetosphere based on convective ExB and VB-curvature particle drift motions. This technique has the advantage of more completely filling out the database and makes maximum use of limited data obtained during high Kp periods or in areas of the magnetosphere with poor satellite flux measurement coverage.

Minow, Joseph I.↗